title={{Local Mixing Determines Spatial Structure of Diahaline Exchange Flow in a Mesotidal Estuary: A Study of Extreme Runoff Conditions}},
volume={54},
year={2024}
}
@article{Blauw2009,
abstract={The set-up, application and validation of a generic ecological model (GEM) for estuaries and coastal waters is presented. This model is a comprehensive ecological model of the bottom of the foodweb, consisting of a set of modules, representing specific water quality processes and primary production that can be combined with any transport model to create a dedicated model for a specific ecosystem. GEM links different physical, chemical and ecological model components into one generic and flexible modelling tool that allows for variable sized, curvilinear grids to accomodate both the requirements for local accuracy while maintaining a relatively short model run-time. The GEM model describes the behaviour of nutrients, organic matter and primary producers in estuaries and coastal waters, incorporating dynamic process modules for dissolved oxygen, nutrients and phytoplankton. GEM integrates the best aspects of existing Dutch estuarine models that were mostly dedicated to only one type of ecosystem, geographic area or subset of processes. Particular strengths of GEM include its generic applicability and the integration and interaction of biological, chemical and physical processes into one predictive tool. The model offers flexibility in choosing which processes to include, and the ability to integrate results from different processes modelled simultaneously with different temporal resolutions. The generic applicability of the model is illustrated using a number of representative examples from case studies in which the GEM model was successfully applied. Validation of these examples was carried out using the 'cost function' to compare model results with field observations. The validation results demonstrated consistent accuracy of the GEM model for various key parameters in both spatial dimensions (horizontally and vertically) as well as temporal dimensions (seasonally and across years) for a variety of water systems without the need for major reparameterisation. {\textcopyright} 2008 Springer Science+Business Media B.V.},
author={Blauw, Anouk N. and Los, Hans F.J. and Bokhorst, Marinus and Erftemeijer, Paul L.A.},
abstract={A new empirical equation is introduced that describes the photosynthesis by phytoplankton as a single, continuous function of available light from the initial linear response through the photoinhibited range at the highest levels liable to be encountered under any natural conditions. The properties of the curve are derived, and a procedure is given for fitting it to the results of light-saturation experiments for phytoplankton. The versatility of the equation is illustrated by data collected on natural phytoplankton assemblages from the eastern Canadian arctic and from the continental shelves of Nova Scotia and Peru.},
author={Platt, T. and Gallegos, C. L. and Harrison, W. G.},
file={:home/og/references/general-references/Photoinhibition of photosynthesis in natural assemblages of marin.pdf:pdf},
issn={00222402},
journal={J. Mar. Res.},
number={4},
pages={687--701},
title={{PHOTOINHIBITION OF PHOTOSYNTHESIS IN NATURAL ASSEMBLAGES OF MARINE PHYTOPLANKTON}},
title={{Photoinhibition of photosynthesis in natural assemblages of marine phytoplankton}},
OxyPOM (Oxygen and Particulate Organic Matter) and DiaMO (Diagnostic Model for Oxygen) are aquatic biogeochemical models that consider key processes for dissolved oxygen (DO) dynamics, such as re-aeration, mineralization, and primary production, in fresh, transitional and marine waters.
Both are implemented in the `Fortran`-based Framework for Aquatic Biogeochemical Models [FABM, @Bruggeman2014] for interoperability in a variety of hydrodynamic models in realistic and idealized applications and for coupleability to other aquatic process models.
With these models, we include an updated light profile implementation and testcases for simulating DO at Cuxhaven Station in the Elbe estuary 2005--2024; for this, we use the General Ocean Turbulence Model (GOTM) [@Burchard2002] for 1D vertical hydrodynamics including tides, and `R` and `bash` scripts for including weather and river data from [kuestendaten.de](https://www.kuestendaten.de).
OxyPOM (Oxygen and Particulate Organic Matter) and DiaMO (Diagnostic Model for Oxygen) are aquatic biogeochemical models that consider key processes for dissolved oxygen (DO)s, such as re-aeration, mineralization, and primary production, in fresh, transitional and marine waters.
Both are implemented in the `Fortran`-based Framework for Aquatic Biogeochemical Models [FABM, @Bruggeman2014] for interoperability in a variety of hydrodynamic models, in realistic and idealized applications, and for coupleability to other aquatic process models.
With these models, we include an updated light profile implementation and testcases for simulating DO at Cuxhaven Station in the Elbe estuary 2005--2024; for this, we use the hydrodynamic General Ocean Turbulence Model (GOTM) [@Burchard2002] including tides, and `R` and `bash` scripts for including weather and river data from [kuestendaten.de](https://www.kuestendaten.de).
We validate both models in the Cuxhaven station in the Elbe estuary, where OxyPOM shows high skill by reproducing surface DO.
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## DiaMO: Diagnostic Model for Oxygen
DiaMO resolves the dynamics of DO, living and non-living organic particulate carbon forms (Phytoplankton and Detritus, respectively) under the assumption that light, not nutrients, is the limiting factor for photosynthesis; DiaMO is a carbon-only implementation.
DiaMO resolves the dynamics of DO, living and non-living organic particulate carbon forms (Phytoplankton (Phy) and Detritus (Det), respectively) under the assumption that light, not nutrients, is the limiting factor for photosynthesis; DiaMO is a carbon-only implementation.
DO is solved with the mass balance equation of OxyPOM (\autoref{eq:do}), setting nitrification to zero.
